SoroushVahidi/scidocs huggingface dataset:
Grasping analysis for a 3-Finger Adaptive Robot Gripper
(2016)

A 3-Finger Adaptive Robot Gripper is an advanced robotic research that provides a robotic hand-like capabilities due to its flexibility and versatility. However, the grasping performance has to be analyzed and monitored based on the motor encoder, motor current, and force feedback so that the finger position and grasping force can be effectively controlled. This paper provides an open-loop grasping analysis for a 3-Finger Adaptive Robot Gripper. A series of grasping tests has been conducted to demonstrate the robot capabilities and functionalities. Different stiffness levels of the grasped objects have been chosen to demonstrate the grasping ability. In the experiment, a Modbus RTU protocol and Matlab/Simulink are used as communication and control platform. A specially modified interlink FSR sensor is proposed where a special plastic cover has been developed to enhance the sensor sensitivity. The Arduino IO Package is employed to interface the sensor and Matlab/Simulink. The results show that the significant relationships between finger position, motor current, and force sensor are found and the results can be used for a proper grasping performance.
Posterior short-segment fixation with or without fusion for thoracolumbar burst fractures. a five to seven-year prospective randomized study.
(2009)

BACKGROUND
The impact of fusion as a supplement to short-segment instrumentation for the treatment of thoracolumbar burst fractures is unclear. We conducted a controlled clinical trial to define the effect of fusion on lumbar spine and patient-related functional outcomes.


METHODS
From 2000 to 2002, seventy-three consecutive patients with a single-level Denis type-B burst fracture involving the thoracolumbar spine and a load-sharing score of <or=6 were managed with posterior pedicle screw instrumentation. The patients were randomly assigned to treatment with posterolateral fusion (fusion group, n = 37) or without posterolateral fusion (nonfusion group, n = 36). The patients were followed for at least five years after surgery and were assessed with regard to clinical and radiographic outcomes. Clinical outcomes were evaluated with use of the Frankel scale, the motor score of the American Spinal Injury Association, a visual analog scale, and the Short Form-36 (SF-36) questionnaire. Radiographic outcomes were assessed on the basis of the local kyphosis angle and loss of kyphosis correction.


RESULTS
No significant difference in radiographic or clinical outcomes was noted between the patients managed with the two techniques. Both operative time and blood loss were significantly less in the nonfusion group compared with the fusion group (p < 0.05). Twenty-five of the thirty-seven patients in the fusion group still had some degree of donor-site pain at the time of the latest examination.


CONCLUSIONS
Posterolateral bone-grafting is not necessary when a Denis type-B thoracolumbar burst fracture associated with a load-sharing score of <or=6 is treated with short-segment pedicle screw fixation.
Ask the Mutants: Mutating Faulty Programs for Fault Localization
(2014)

We present MUSE (MUtation-baSEd fault localization technique), a new fault localization technique based on mutation analysis. A key idea of MUSE is to identify a faulty statement by utilizing different characteristics of two groups of mutants-one that mutates a faulty statement and the other that mutates a correct statement. We also propose a new evaluation metric for fault localization techniques based on information theory, called Locality Information Loss (LIL): it can measure the aptitude of a localization technique for automated fault repair systems as well as human debuggers. The empirical evaluation using 14 faulty versions of the five real-world programs shows that MUSE localizes a fault after reviewing 7.4 statements on average, which is about 25 times more precise than the state-of-the-art SBFL technique Op2.
APAC: Augmented PAttern Classification with Neural Networks
(2015)

Deep neural networks have been exhibiting splendid accuracies in many of visual pattern classification problems. Many of the state-of-the-art methods employ a technique known as data augmentation at the training stage. This paper addresses an issue of decision rule for classifiers trained with augmented data. Our method is named as APAC: the Augmented PAttern Classification, which is a way of classification using the optimal decision rule for augmented data learning. Discussion of methods of data augmentation is not our primary focus. We show clear evidences that APAC gives far better generalization performance than the traditional way of class prediction in several experiments. Our convolutional neural network model with APAC achieved a state-of-the-art accuracy on the MNIST dataset among non-ensemble classifiers. Even our multilayer perceptron model beats some of the convolutional models with recentlyinvented stochastic regularization techniques on the CIFAR10 dataset.
Graphene-based single-bacterium resolution biodevice and DNA transistor: interfacing graphene derivatives with nanoscale and microscale biocomponents.
(2008)

Establishing "large-contact-area" interfaces of sensitive nanostructures with microbes and mammalian cells will lead to the development of valuable tools and devices for biodiagnostics and biomedicine. Chemically modified graphene (CMG) nanostructures with their microscale area, sensitive electrical properties, and modifiable chemical functionality are excellent candidates for such biodevices at both biocellular and biomolecular scale. Here, we report on the fabrication and functioning of a novel CMG-based (i) single-bacterium biodevice, (ii) label-free DNA sensor, and (iii) bacterial DNA/protein and polyelectrolyte chemical transistor. The bacteria biodevice was highly sensitive with a single-bacterium attachment generating approximately 1400 charge carriers in a p-type CMG. Similarly, single-stranded DNA tethered on graphene hybridizes with its complementary DNA strand to reversibly increase the hole density by 5.61 x 1012 cm(-2). We further demonstrate (a) a control on the device sensitivity by manipulating surface groups, (b) switching of polarity specificity by changing surface polarity, and (c) a preferential attachment of DNA on thicker CMG surfaces and sharp CMG wrinkles.
Discriminative key-component models for interaction detection and recognition
(2015)

Not all frames are equal – selecting a subset of discriminative frames from a video can improve performance at detecting and recognizing human interactions. In this paper we present models for categorizing a video into one of a number of predefined interactions or for detecting these interactions in a long video sequence. The models represent the interaction by a set of key temporal moments and the spatial structures they entail. For instance: two people approaching each other, then extending their hands before engaging in a “handshaking” interaction. Learning the model parameters requires only weak supervision in the form of an overall label for the interaction. Experimental results on the UT-Interaction and VIRAT datasets verify the efficacy of these structured models for human interactions.
Why Are Consumers Willing to Pay for Privacy? An Application of the Privacy-freemium Model to Media Companies
(2015)

Monetizing their users’ personal information instead of charging a fee has become an established revenue model for platform operators—a new form of media companies specialized in aggregating, managing, and distributing user-generated online content. However, the commodification of privacy leads to privacy concerns that might be a risk for such businesses. Thus, a new approach is to focus on consumers’ willingness to pay for privacy, assuming that monetizing privacy protection might be an alternative revenue model. Following the freemium idea, we developed an innovative research design, offering 553 online survey participants the opportunity to subscribe to a fictional premium version of Facebook with additional privacy control features in return for a monthly fee. Based on the theory of planned behavior, we developed and tested a research model to explain actual willingness to pay for privacy behavior. Our findings show that perceived usefulness and trust significantly affect willingness to pay. In contrast, perceived internet privacy risk was not found to have a significant influence. We thus conclude that consumers are willing to pay for privacy in the form of a privacy-freemium model, provided they perceive the premium version as offering added value and as trustworthy.
Decision support system for servitization of industrial SMEs: a modelling and simulation approach
(2015)

Decision support system for servitization of industrial SMEs: a modelling and simulation approach M. Chalal, X. Boucher & G. Marques To cite this article: M. Chalal, X. Boucher & G. Marques (2015) Decision support system for servitization of industrial SMEs: a modelling and simulation approach, Journal of Decision Systems, 24:4, 355-382, DOI: 10.1080/12460125.2015.1074836 To link to this article: http://dx.doi.org/10.1080/12460125.2015.1074836
A neurophilosophical slant on consciousness research.
(2005)

Explaining the nature and mechanisms of conscious experience in neurobiological terms seems to be an attainable, if yet unattained, goal. Research at many levels is important, including research at the cellular level that explores the role of recurrent pathways between thalamic nuclei and the cortex, and research that explores consciousness from the perspective of action. Conceptually, a clearer understanding of the logic of expressions such as "causes" and "correlates", and about what to expect from a theory of consciousness are required. The logic of some terms, such as "qualia" and "reductionism", continues to generate misunderstandings about the scientific possibilities and limits. Experimentally, a deeper understanding of the role of the thalamus in coordinating activity across cortical levels, and a readiness to reconsider the orthodox approach to thalamocortical organization are also required.
TopicViz: interactive topic exploration in document collections
(2012)

Existing methods for searching and exploring large document collections focus on surface-level matches to user queries, ignoring higher-level semantic structure. In this paper we show how topic modeling - a technique for identifying latent themes across a large collection of documents - can support semantic exploration. We present TopicViz: an interactive environment which combines traditional search and citation-graph exploration with a force-directed layout that links documents to the latent themes discovered by the topic model. We describe usage scenarios in which TopicViz supports rapid sensemaking on large document collections.
Moving Obstacle Detection using Monocular Vision
(2006)

This paper proposes a method for detecting moving obstacles on roads, by using a vehicle mounted monocular camera. To detect various moving obstacles, such as vehicles and pedestrians, the ego-motion of the vehicle is initially estimated from images captured by the camera. There are two problems in ego-motion estimation. Firstly, a typical road scene contains moving obstacles. This causes false estimation of the ego-motion. Secondly, roads possess fewer features, when compared to the number associated with background structures. This reduces the accuracy of ego-motion estimation. In our approach, the ego-motion is estimated from the correspondences of dispersed feature points extracted from various regions other than those that contain moving obstacles. After estimating the ego-motion, any moving obstacles are detected by tracking the feature points over consecutive frames. In our experiments, it has been shown that the proposed method is able to detect moving obstacles
A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem
(2007)

Over the last decade many metaheuristics have been applied t o the flowshop scheduling problem, ranging from Simulated Annealing or Tabu Search to complex hybrid techniques. Some of these methods provide excellent effectiveness and e fficiency at the expense of being utterly complicated. In fact, several published meth ods require substantial implementation efforts, exploit problem specific speed-up techniqu es that cannot be applied to slight variations of the original problem, and often re-implement ations of these methods by other researchers produce results that are quite different from t he original ones. In this work we present a new iterated greedy algorithm that applies two pha ses iteratively, namedestruction, were some jobs are eliminated from the incumbent solution, andconstruction, where the eliminated jobs are reinserted into the sequence using t he well known NEH construction Corresponding author
An Overview of Virtual Machine Architectures
(2004)

hen early computer systems were being developed, hardware was designed first and software written specifically for that hardware followed. Each system was essentially handcrafted with its own instruction set, and software was developed for that specific instruction set. This included operating system software, assemblers (later compilers), and application programs. With a small user community, relatively simple programs, and fixed hardware, this tightly integrated approach worked quite well, especially while the basic concepts of the stored program computer were still evolving. But user communities grew, operating systems became more complex, and the number of application programs rapidly expanded, so that re-writing and distributing software for each new computer system became a major burden.
Human simulations of vocabulary learning
(1999)

The work reported here experimentally investigates a striking generalization about vocabulary acquisition: Noun learning is superior to verb learning in the earliest moments of child language development. The dominant explanation of this phenomenon in the literature invokes differing conceptual requirements for items in these lexical categories: Verbs are cognitively more complex than nouns and so their acquisition must await certain mental developments in the infant. In the present work, we investigate an alternative hypothesis; namely, that it is the information requirements of verb learning, not the conceptual requirements, that crucially determine the acquisition order. Efficient verb learning requires access to structural features of the exposure language and thus cannot take place until a scaffolding of noun knowledge enables the acquisition of clause-level syntax. More generally, we experimentally investigate the hypothesis that vocabulary acquisition takes place via an incremental constraint-satisfaction procedure that bootstraps itself into successively more sophisticated linguistic representations which, in turn, enable new kinds of vocabulary learning. If the experimental subjects were young children, it would be difficult to distinguish between this information-centered hypothesis and the conceptual change hypothesis. Therefore the experimental "learners" are adults. The items to be "acquired" in the experiments were the 24 most frequent nouns and 24 most frequent verbs from a sample of maternal speech to 18-24-month-old infants. The various experiments ask about the kinds of information that will support identification of these words as they occur in mother-to-child discourse. Both the proportion correctly identified and the type of word that is identifiable changes significantly as a function of information type. We discuss these results as consistent with the incremental construction of a highly lexicalized grammar by cognitively and pragmatically sophisticated human infants, but inconsistent with a procedure in which lexical acquisition is independent of and antecedent to syntax acquisition.
Why Nouns Are Learned before Verbs: Linguistic Relativity Versus Natural Partitioning. Technical Report No. 257.
(1982)

ABSTRACT There is overwhelming evidence that children's first words are primarily nouns even across languages. These data are interpreted as evidence of a "Natural Partitions Theory," one that holds that the concepts referred to by nouns are conceptually more basic than those referred to by verbs or prepositions. Analysis of data from cross-linguistic studies designed to eliminate Inonconceptual differences between words in a language that might account for the Larlier acquisition of nouns--such as the position of a word in the sentence, morphological transparency (the ease with which the root can be heard in various uses of the word), and patterns of language teaching strategies--leaves some version of the Natural Partitions hypothesis as the most reasonable view of early vocabulary acquisition. A cross-linguistic examination of a single sentence suggests that if objecthood is created by spatial relations among perceptual elements, then good concrete objects are particularly cohesive collections of percepts. These highly cohesive collections of perceptual information tend to be lexicalized as nouns by almost every language. Object concepts are given to language users by the world and can be learned one at a time, while predicate concepts form a system in each language., that, from a child's point of view, must be discovered. (HTE)
FROM SIMPLE ASSOCIATIONS TO SYSTEMATIC REASONING : A Connectionist representation of rules , variables , and dynamic bindings using temporal synchrony
(1993)

Human agents draw a variety of inferences effortlessly, spontaneously, and with remarkable efficiency — as though these inferences are a reflex response of their cognitive apparatus. Furthermore, these inferences are drawn with reference to a large body of background knowledge. This remarkable human ability seems paradoxical given the results about the complexity of reasoning reported by researchers in artificial intelligence. It also poses a challenge for cognitive science and computational neuroscience: How can a system of simple and slow neuron-like elements represent a large body of systematic knowledge and perform a range of inferences with such speed? We describe a computational model that is a step toward addressing the cognitive science challenge and resolving the artificial intelligence paradox. We show how a connectionist network can encode millions of facts and rules involving n-ary predicates and variables, and perform a class of inferences in a few hundred msec. Efficient reasoning requires the rapid representation and propagation of dynamic bindings. Our model achieves this by i) representing dynamic bindings as the synchronous firing of appropriate nodes, ii) rules as interconnection patterns that direct the propagation of rhythmic activity, iii) and long-term facts as temporal pattern-matching sub-networks. The model is consistent with recent neurophysiological findings which suggest that synchronous activity occurs in the brain and may play a representational role in neural information processing. The model also makes specific predictions about the nature of reflexive reasoning that are psychologically significant. It identifies constraints on the form of rules that may participate in such reasoning and relates the capacity of the working memory underlying reflexive reasoning to biological parameters such as the lowest frequency at which nodes can sustain synchronous oscillations and the coarseness of synchronization.
Zero-Shot Adaptive Transfer for Conversational Language Understanding
(2019)

Conversational agents such as Alexa and Google Assistant constantly need to increase their language understanding capabilities by adding new domains. A massive amount of labeled data is required for training each new domain. While domain adaptation approaches alleviate the annotation cost, prior approaches suffer from increased training time and suboptimal concept alignments. To tackle this, we introduce a novel Zero-Shot Adaptive Transfer method for slot tagging that utilizes the slot description for transferring reusable concepts across domains, and enjoys efficient training without any explicit concept alignments. Extensive experimentation over a dataset of 10 domains relevant to our commercial personal digital assistant shows that our model outperforms previous state-of-the-art systems by a large margin, and achieves an even higher improvement in the low data regime.
Type Checking Type Classes
(1993)

We study the type inference problem for a system with type classes as in the functional programming language Haskell. Type classes are an extension of ML-style polymorphism with overloading. We generalize Milner's work on polymorphism by introducing a separate context constraining the type variables in a typing judgement. This lead to simple type inference systems and algorithms which closely resemble those for ML. In particular we present a new unification algorithm which is an extension of syntactic unification with constraint solving. The existence of principal types follows from an analysis of this unification algorithm.
Gender violence: transgender experiences with violence and discrimination.
(2001)

There is a pervasive pattern of discrimination and prejudice against transgendered people within society. Both economic discrimination and experiencing violence could be the result of a larger social climate that severely sanctions people for not conforming to society's norms concerning gender; as such, both would be strongly associated with each other. Questionnaires were distributed to people either through events or through volunteers, and made available upon the World Wide Web. A sample of 402 cases was collected over the span of 12 months (April 1996-April 1997). We found that over half the people within this sample experienced some form of harassment or violence within their lifetime, with a quarter experiencing a violent incident. Further investigation found that experiencing economic discrimination because one is transgendered had the strongest association with experiencing a transgender related violent incident. Economic discrimination was related to transgendered people's experience with violence. Therefore, both hate crimes legislation and employment protections are needed for transgendered individuals.